mHistogram(1)


NAME

   mHistogram - None

SYNOPSIS

   mHistogram      [-d]      -file      in.fits      minrange     maxrange
   [logpower/gaussian/gaussian-log] -out out.hist

DESCRIPTION

   The mViewer application makes  PNG/JPEG  files  using  FITS  images  as
   input.   Part  of that processing involves analyzing the FITS files and
   creating a histogram that is used to  inform  the  transformation  from
   pixel  values  to  display colors/intensities.  This processing is done
   inside mViewer itself.

   However, there are situations where it  helps  to  have  the  histogram
   earlier.   For  instance,  you  may have several images to process into
   PNGs and wish to use the same histogram-based stretch for each one.  Or
   you  may  want  to  generate a set of pixel values that give the visual
   impression of a color bar (see mPad). Sometimes, you may just want  the
   histogram itself for display or analysis purposes.

   The  mHistogram  module contains the same histogram code as mViewer but
   writes the results out to an ASCII file which can then be  read  in  by
   mHistogram, mPad or user programs.

OPTIONS

   -d     Turn on debugging.

   -file in.fits minrange maxrange [logpower/gaussian/gaussian-log]
          The  FITS  image  file;  stretch range; and (optionally) stretch
          mode.  See the mViewer documentation for more details.

   -out out.hist
          Output histogram (ASCII) file.

RESULT

   If successful, the result is an ASCII  file  containing  the  histogram
   data, color table lookup mapping, and some other information.

MESSAGES

   ERROR  Too few arguments following -file flag

   ERROR  Image file badfile invalid FITS

   ERROR  Can't find HDU badHDU

   ERROR  Too few arguments following -out flag

   ERROR  No input FITS file name given

   ERROR  No output histogram file name given

   ERROR  Cannot open output histogram file.

   ERROR  Grayscale/pseudocolor mode but no gray image given

   ERROR  FITS library error

   ERROR  leading  numeric  term  in   'string'  cannot  be converted to a
          finite floating point number

   ERROR  is not a valid datatype

   ERROR  negative percentile

   ERROR  percentile context larger than 100

   ERROR  extra numeric term in context 'string'  cannot be converted to a
          finite floating point number

   ERROR  context 'string' contains trailing junk

EXAMPLES

   mHistogram -file SDSS_r.fits -2s max gaussian-log -out SDSS_r.hist
          [struct stat="OK"]

BUGS

   The  drizzle  algorithm has been implemented but has not been tested in
   this release.

   If a header template contains carriage returns (i.e.,  created/modified
   on  a  Windows  machine), the cfitsio library will be unable to read it
   properly, resulting in the  error:  [struct  stat="ERROR",  status=207,
   msg="illegal character in keyword"]

   It  is  best  for  the  background  correction  algorithms  if the area
   described in the header template completely encloses all of  the  input
   images in their entirety. If parts of input images are "chopped off" by
   the header template, the background correction  will  be  affected.  We
   recommend   you  use  an  expanded  header  for  the  reprojection  and
   background modeling steps, returning to the originally  desired  header
   size  for the final coaddition. The default background matching assumes
   that there are no non-linear background variations  in  the  individual
   images  (and  therefore  in  the  overlap differences). If there is any
   uncertainty in this regard, it is safer to turn  on  the  "level  only"
   background matching (the "-l" flag in mBgModel.

COPYRIGHT

   2001-2015 California Institute of Technology, Pasadena, California

   If   your   research   uses   Montage,  please  include  the  following
   acknowledgement: "This research made use of Montage. It  is  funded  by
   the National Science Foundation under Grant Number ACI-1440620, and was
   previously   funded   by   the   National   Aeronautics    and    Space
   Administration's   Earth   Science   Technology   Office,   Computation
   Technologies  Project,  under  Cooperative  Agreement  Number  NCC5-626
   between NASA and the California Institute of Technology."

   The  Montage distribution includes an adaptation of the MOPEX algorithm
   developed at the Spitzer Science Center.





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